Editorial

3 pages, 132 KiB

Open AccessEditorial

Innovations in Chest Imaging: How Can Patients Benefit?

by Christian Booz

Diagnostics 2024, 14(2), 141; https://doi.org/10.3390/diagnostics14020141 - 08 Jan 2024

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This Special Issue of Diagnostics entitled “Leading Diagnosis on Chest Imaging” provides an overview of recent technical developments in chest imaging and their clinical relevance, with a special focus on dual-energy CT (DECT) imaging [...] Full article

(This article belongs to the Special Issue Leading Diagnosis on Chest Imaging)

Research

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12 pages, 2273 KiB

Open AccessArticle

Improved Coronary Artery Visualization Using Virtual Monoenergetic Imaging from Dual-Layer Spectral Detector CT Angiography

by Tommaso D’Angelo, Ludovica R. M. Lanzafame, Antonino Micari, Alfredo Blandino, Ibrahim Yel, Vitali Koch, Leon D. Gruenewald, Thomas J. Vogl, Christian Booz, Giuseppe M. Bucolo, Maria Teresa Cannizzaro, Giorgio Ascenti and Silvio Mazziotti

Diagnostics 2023, 13(16), 2675; https://doi.org/10.3390/diagnostics13162675 - 14 Aug 2023

Cited by 4 | Viewed by 860

Abstract

Background: To evaluate if coronary CT angiography (CCTA) monoenergetic reconstructions, obtained with a dual-layer spectral detector computed tomography (DLCT) system, offer improved image quality compared with 120 kVp conventional images without affecting the quantitative assessment of coronary stenoses. Methods: Fifty CCTA [...] Read more.

Background: To evaluate if coronary CT angiography (CCTA) monoenergetic reconstructions, obtained with a dual-layer spectral detector computed tomography (DLCT) system, offer improved image quality compared with 120 kVp conventional images without affecting the quantitative assessment of coronary stenoses. Methods: Fifty CCTA datasets (30 men; mean age: 61.6 ± 12.3 years) acquired with a DLCT system were reconstructed using virtual monoenergetic images (VMI) from 40 to 100 keV with 10 keV increment and compared with conventional images. An analysis of objective image quality was performed, evaluating the signal- and contrast-to-noise ratio. For the subjective assessment, two readers used a 5-point Likert scoring system to evaluate sharpness, noise, demarcation of coronary plaques, vascular contrast, and an overall score. Furthermore, coronary stenoses were analyzed for each vessel to describe the diagnostic agreement between monoenergetic images and conventional images. Results: The objective image analysis showed that all reconstructions from 70 keV to 40 keV show higher SNR (from 61.33 ± 12.46 to 154.22 ± 42.91, respectively) and CNR (from 51.45 ± 11.19 to 135.63 ± 39.38, respectively) compared with conventional images (all p < 0.001). The 40 keV monoenergetic images obtained the best average score for sharpness, vascular contrast, and for the overall impression (all with p < 0.001). The detection and grading of stenoses of the coronary arteries with conventional and monoenergetic images at 70 keV and 40 keV showed an overall excellent interobserver agreement (k= 0.81 [0.72–0.91]). Conclusions: The 40 keV virtual monoenergetic images obtained with a DLCT system allow the objective and subjective image quality of coronary CT angiography to be improved. Full article

(This article belongs to the Special Issue Leading Diagnosis on Chest Imaging)

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13 pages, 30347 KiB

Open AccessArticle

Tumor Lung Visualization and Localization through Virtual Reality and Thermal Feedback Interface

by Samir Benbelkacem, Nadia Zenati-Henda, Nabil Zerrouki, Adel Oulefki, Sos Agaian, Mostefa Masmoudi, Ahmed Bentaleb and Alex Liew

Diagnostics 2023, 13(3), 567; https://doi.org/10.3390/diagnostics13030567 - 03 Feb 2023

Cited by 3 | Viewed by 1949

Abstract

The World Health Organization estimates that there were around 10 million deaths due to cancer in 2020, and lung cancer was the most common type of cancer, with over 2.2 million new cases and 1.8 million deaths. While there have been advances in [...] Read more.

The World Health Organization estimates that there were around 10 million deaths due to cancer in 2020, and lung cancer was the most common type of cancer, with over 2.2 million new cases and 1.8 million deaths. While there have been advances in the diagnosis and prediction of lung cancer, there is still a need for new, intelligent methods or diagnostic tools to help medical professionals detect the disease. Since it is currently unable to detect at an early stage, speedy detection and identification are crucial because they can increase a patient’s chances of survival. This article focuses on developing a new tool for diagnosing lung tumors and providing thermal touch feedback using virtual reality visualization and thermal technology. This tool is intended to help identify and locate tumors and measure the size and temperature of the tumor surface. The tool uses data from CT scans to create a virtual reality visualization of the lung tissue and includes a thermal display incorporated into a haptic device. The tool is also tested by touching virtual tumors in a virtual reality application. On the other hand, thermal feedback could be used as a sensory substitute or adjunct for visual or tactile feedback. The experimental results are evaluated with the performance comparison of different algorithms and demonstrate that the proposed thermal model is effective. The results also show that the tool can estimate the characteristics of tumors accurately and that it has the potential to be used in a virtual reality application to “touch” virtual tumors. In other words, the results support the use of the tool for diagnosing lung tumors and providing thermal touch feedback using virtual reality visualization, force, and thermal technology. Full article

(This article belongs to the Special Issue Leading Diagnosis on Chest Imaging)

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17 pages, 1357 KiB

Open AccessArticle

An Efficient Deep Learning Method for Detection of COVID-19 Infection Using Chest X-ray Images

by Soumya Ranjan Nayak, Deepak Ranjan Nayak, Utkarsh Sinha, Vaibhav Arora and Ram Bilas Pachori

Diagnostics 2023, 13(1), 131; https://doi.org/10.3390/diagnostics13010131 - 30 Dec 2022

Cited by 19 | Viewed by 2129

Abstract

The research community has recently shown significant interest in designing automated systems to detect coronavirus disease 2019 (COVID-19) using deep learning approaches and chest radiography images. However, state-of-the-art deep learning techniques, especially convolutional neural networks (CNNs), demand more learnable parameters and memory. Therefore, [...] Read more.

The research community has recently shown significant interest in designing automated systems to detect coronavirus disease 2019 (COVID-19) using deep learning approaches and chest radiography images. However, state-of-the-art deep learning techniques, especially convolutional neural networks (CNNs), demand more learnable parameters and memory. Therefore, they may not be suitable for real-time diagnosis. Thus, the design of a lightweight CNN model for fast and accurate COVID-19 detection is an urgent need. In this paper, a lightweight CNN model called LW-CORONet is proposed that comprises a sequence of convolution, rectified linear unit (ReLU), and pooling layers followed by two fully connected layers. The proposed model facilitates extracting meaningful features from the chest X-ray (CXR) images with only five learnable layers. The proposed model is evaluated using two larger CXR datasets (Dataset-1: 2250 images and Dataset-2: 15,999 images) and the classification accuracy obtained are 98.67% and 99.00% on Dataset-1 and 95.67% and 96.25% on Dataset-2 for multi-class and binary classification cases, respectively. The results are compared with four contemporary pre-trained CNN models as well as state-of-the-art models. The effect of several hyperparameters: different optimization techniques, batch size, and learning rate have also been investigated. The proposed model demands fewer parameters and requires less memory space. Hence, it is effective for COVID-19 detection and can be utilized as a supplementary tool to assist radiologists in their diagnosis. Full article

(This article belongs to the Special Issue Leading Diagnosis on Chest Imaging)

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12 pages, 974 KiB

Open AccessArticle

Well-Aerated Lung and Mean Lung Density Quantified by CT at Discharge to Predict Pulmonary Diffusion Function 5 Months after COVID-19

by Leqing Chen, Feihong Wu, Jia Huang, Jinrong Yang, Wenliang Fan, Zhuang Nie, Hongwei Jiang, Jiazheng Wang, Wenfang Xia and Fan Yang

Diagnostics 2022, 12(12), 2921; https://doi.org/10.3390/diagnostics12122921 - 23 Nov 2022

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Abstract

Background: The aim of this study was to explore the predictive values of quantitative CT indices of the total lung and lung lobe tissue at discharge for the pulmonary diffusion function of coronavirus disease 2019 (COVID-19) patients at 5 months after symptom onset. [...] Read more.

Background: The aim of this study was to explore the predictive values of quantitative CT indices of the total lung and lung lobe tissue at discharge for the pulmonary diffusion function of coronavirus disease 2019 (COVID-19) patients at 5 months after symptom onset. Methods: A total of 90 patients with moderate and severe COVID-19 underwent CT scans at discharge, and pulmonary function tests (PFTs) were performed 5 months after symptom onset. The differences in quantitative CT and PFT results between Group 1 (patients with abnormal diffusion function) and Group 2 (patients with normal diffusion function) were compared by the chi-square test, Fisher’s exact test or Mann–Whitney U test. Univariate analysis, stepwise linear regression and logistic regression were used to determine the predictors of diffusion function in convalescent patients. Results: A total of 37.80% (34/90) of patients presented diffusion dysfunction at 5 months after symptom onset. The mean lung density (MLD) of the total lung tissue in Group 1 was higher than that in Group 2, and the percentage of the well-aerated lung (WAL) tissue volume (WAL%) of Group 1 was lower than that of Group 2 (all p < 0.05). Multiple stepwise linear regression identified only WAL and WAL% of the left upper lobe (LUL) as parameters that positively correlated with the percent of the predicted value of diffusion capacity of the lungs for carbon monoxide (WAL: p = 0.002; WAL%: p = 0.004), and multiple stepwise logistic regression identified MLD and MLD_LUL as independent predictors of diffusion dysfunction (MLD: OR (95%CI): 1.011 (1.001, 1.02), p = 0.035; MLD_LUL: OR (95%CI): 1.016 (1.004, 1.027), p = 0.008). Conclusion: At five months after symptom onset, more than one-third of moderate and severe COVID-19 patients presented with diffusion dysfunction. The well-aerated lung and mean lung density quantified by CT at discharge could be predictors of diffusion function in convalesce. Full article

(This article belongs to the Special Issue Leading Diagnosis on Chest Imaging)

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8 pages, 599 KiB

Open AccessArticle

Evaluation of Patients Who Developed Pneumothorax Due to COVID-19

by Gökhan Çoraplı and Veysi Tekin

Diagnostics 2022, 12(9), 2140; https://doi.org/10.3390/diagnostics12092140 - 02 Sep 2022

Cited by 1 | Viewed by 1340

Abstract

Background: Although SARS-CoV-2 infection often affects the lungs, pneumothorax is extremely rare. The aim of this study was to analyze the characteristics of patients who were hospitalized due to COVID-19 and who developed pneumothorax (PNX) and to analyze their risk factors. Methods: Patients [...] Read more.

Background: Although SARS-CoV-2 infection often affects the lungs, pneumothorax is extremely rare. The aim of this study was to analyze the characteristics of patients who were hospitalized due to COVID-19 and who developed pneumothorax (PNX) and to analyze their risk factors. Methods: Patients who developed PNX, among the patients who were followed up in the hospital due to COVID-19 between 1 April 2020 and 1 April 2022, were included in the study. The mean and standard deviation values of the descriptive statistics were obtained from patient data. The entire application was carried out using IBM SPSS 26 (IBM Corp., Armonk, NY, USA). p values < 0.05 were considered statistically significant. Results: We observed that advanced age and male gender increase the risk of COVID-19 patientsdeveloping PNX, but smoking, sepsis, and being followed-up with mechanical ventilation do not increase this risk. In addition, we observed that the presence of an additional disease increases the mortality rate. Conclusion: We show that advanced age and male gender increase the risk for PNX, which is a rare complication of COVID-19, and that comorbidity is associated with mortality in these patients. Full article

(This article belongs to the Special Issue Leading Diagnosis on Chest Imaging)

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Review

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21 pages, 5903 KiB

Open AccessReview

Dual-Energy CT in Cardiothoracic Imaging: Current Developments

by Leona S. Alizadeh, Thomas J. Vogl, Stephan S. Waldeck, Daniel Overhoff, Tommaso D’Angelo, Simon S. Martin, Ibrahim Yel, Leon D. Gruenewald, Vitali Koch, Florian Fulisch and Christian Booz

Diagnostics 2023, 13(12), 2116; https://doi.org/10.3390/diagnostics13122116 - 19 Jun 2023

Cited by 7 | Viewed by 2422

Abstract

This article describes the technical principles and clinical applications of dual-energy computed tomography (DECT) in the context of cardiothoracic imaging with a focus on current developments and techniques. Since the introduction of DECT, different vendors developed distinct hard and software approaches for generating [...] Read more.

This article describes the technical principles and clinical applications of dual-energy computed tomography (DECT) in the context of cardiothoracic imaging with a focus on current developments and techniques. Since the introduction of DECT, different vendors developed distinct hard and software approaches for generating multi-energy datasets and multiple DECT applications that were developed and clinically investigated for different fields of interest. Benefits for various clinical settings, such as oncology, trauma and emergency radiology, as well as musculoskeletal and cardiovascular imaging, were recently reported in the literature. State-of-the-art applications, such as virtual monoenergetic imaging (VMI), material decomposition, perfused blood volume imaging, virtual non-contrast imaging (VNC), plaque removal, and virtual non-calcium (VNCa) imaging, can significantly improve cardiothoracic CT image workflows and have a high potential for improvement of diagnostic accuracy and patient safety. Full article

(This article belongs to the Special Issue Leading Diagnosis on Chest Imaging)

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Other

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7 pages, 2910 KiB

Open AccessCase Report

Multi-Contrast Differentiation by Dual-Energy Spectral CT Angiography in a Patient with Pulmonary Barium Granulomas

by Tommaso D’Angelo, Francesco M. Arico, Lydia Broccio, Giorgio Ascenti, Silvio Mazziotti, Christian Booz, Simon S. Martin, Ibrahim Yel, Ludovica R. M. Lanzafame, Alfredo Blandino and Carmelo Sofia

Diagnostics 2023, 13(5), 832; https://doi.org/10.3390/diagnostics13050832 - 22 Feb 2023

Cited by 1 | Viewed by 1456

Abstract

Barium inhalation usually relates to accidental aspiration during radiological procedures with an oral contrast agent. When present, barium lung deposits are visible as high-density opacities on chest X-ray or CT scan due to high atomic number, and they may be indistinguishable from calcifications. [...] Read more.

Barium inhalation usually relates to accidental aspiration during radiological procedures with an oral contrast agent. When present, barium lung deposits are visible as high-density opacities on chest X-ray or CT scan due to high atomic number, and they may be indistinguishable from calcifications. Dual-layer spectral CT has shown good material differentiation capabilities, due to its increased high-Z element range and smaller spectral separation between low- and high-energy spectral data. We present the case of a 17-year-old female with a history of tracheoesophageal fistula, who underwent chest CT angiography on a dual-layer spectral platform. Despite the close Z numbers and K-edge energy levels of the two different contrast materials, spectral CT was able to identify barium lung deposits from a previous swallowing study and to clearly distinguish them from calcium and the surrounding iodine-containing structures. Full article

(This article belongs to the Special Issue Leading Diagnosis on Chest Imaging)

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5 pages, 1433 KiB

Open AccessInteresting Images

Diagnosis of an Acute Anterior Wall Infarction in Dual-Energy CT

by Aynur Gökduman, Ibrahim Yel, Thomas J. Vogl, Mirela Dimitrova, Leon D. Grünewald, Vitali Koch, Leona S. Alizadeh, Andreas S. Brendlin, Ahmed E. Othman, Simon S. Martin, Tommaso D’Angelo, Alfredo Blandino, Silvio Mazziotti and Christian Booz

Diagnostics 2023, 13(4), 761; https://doi.org/10.3390/diagnostics13040761 - 17 Feb 2023

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Abstract

Due to its high morbidity and mortality, myocardial infarction is the leading cause of death worldwide. Against this background, rapid diagnosis is of immense importance. Especially in case of an atypical course, the correct diagnosis may be delayed and thus lead to increased [...] Read more.

Due to its high morbidity and mortality, myocardial infarction is the leading cause of death worldwide. Against this background, rapid diagnosis is of immense importance. Especially in case of an atypical course, the correct diagnosis may be delayed and thus lead to increased mortality rates. In this report, we present a complex case of acute coronary syndrome. A triple-rule-out CT examination was performed in dual-energy CT (DECT) mode. While pulmonary artery embolism and aortic dissection could be ruled out with conventional CT series, the presence of anterior wall infarction was only detectable on DECT reconstructions. Subsequently, adequate and rapid therapy was then initiated leading to survival of the patient. Full article

(This article belongs to the Special Issue Leading Diagnosis on Chest Imaging)

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4 pages, 3463 KiB

Open AccessInteresting Images

Spectral CT Imaging of Prosthetic Valve Embolization after Transcatheter Aortic Valve Implantation

by Tommaso D’Angelo, Giampiero Vizzari, Ludovica R. M. Lanzafame, Federica Pergolizzi, Silvio Mazziotti, Michele Gaeta, Francesco Costa, Gianluca Di Bella, Thomas J. Vogl, Christian Booz, Antonio Micari and Alfredo Blandino

Diagnostics 2023, 13(4), 678; https://doi.org/10.3390/diagnostics13040678 - 11 Feb 2023

Cited by 2 | Viewed by 1425

Abstract

Transcatheter heart valve (THV) embolization is a rare complication of transcatheter aortic valve implantation (TAVI) generally caused by malpositioning, sizing inaccuracies and pacing failures. The consequences are related to the site of embolization, ranging from a silent clinical picture when the device is [...] Read more.

Transcatheter heart valve (THV) embolization is a rare complication of transcatheter aortic valve implantation (TAVI) generally caused by malpositioning, sizing inaccuracies and pacing failures. The consequences are related to the site of embolization, ranging from a silent clinical picture when the device is stably anchored in the descending aorta to potentially fatal outcomes (e.g., obstruction of flow to vital organs, aortic dissection, thrombosis, etc.). Here, we present the case of a 65-year-old severely obese woman affected by severe aortic valve stenosis who underwent TAVI complicated by embolization of the device. The patient underwent spectral CT angiography that allowed for improved image quality by means of virtual monoenergetic reconstructions, permitting optimal pre-procedural planning. She was successfully re-treated with implantation of a second prosthetic valve a few weeks later. Full article

(This article belongs to the Special Issue Leading Diagnosis on Chest Imaging)

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